Merge branch 'bordel_laurent' of git.inpt.fr:tocard-inc/enseeiht/projet-be into bordel_laurent

This commit is contained in:
Laureηt 2023-01-31 21:15:37 +01:00
commit 46986390e9
Signed by: Laurent
SSH key fingerprint: SHA256:kZEpW8cMJ54PDeCvOhzreNr4FSh6R13CMGH/POoO8DI
3 changed files with 277 additions and 23 deletions

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@ -2,11 +2,9 @@ import numpy as np
import matplotlib.pyplot as plt
def update_border(voxel_values, idx=None):
def update_border(voxel_values):
voxel_values = voxel_values > 0
if idx is None:
if len(voxel_values.shape) == 3:
x_m1 = voxel_values[1:, :, :]
x_m1 = np.concatenate((x_m1, np.zeros((1, x_m1.shape[1], x_m1.shape[2]))), axis=0)
@ -36,7 +34,27 @@ def update_border(voxel_values, idx=None):
)
)
# TODO: update only concidered voxels (idx)
elif len(voxel_values.shape) == 2:
x_m1 = voxel_values[1:, :]
x_m1 = np.concatenate((x_m1, np.zeros((1, x_m1.shape[1]))), axis=0)
x_p1 = voxel_values[:-1, :]
x_p1 = np.concatenate((np.zeros((1, x_p1.shape[1])), x_p1), axis=0)
y_m1 = voxel_values[:, 1:]
y_m1 = np.concatenate((y_m1, np.zeros((y_m1.shape[0], 1))), axis=1)
y_p1 = voxel_values[:, :-1]
y_p1 = np.concatenate((np.zeros((y_p1.shape[0], 1)), y_p1), axis=1)
return np.logical_or.reduce(
(
voxel_values != x_m1,
voxel_values != x_p1,
voxel_values != y_m1,
voxel_values != y_p1,
)
)
if __name__ == "__main__":

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@ -1,5 +1,6 @@
import matplotlib.pyplot as plt
import numpy as np
import cv2
def f(x, y):
@ -16,17 +17,15 @@ Z = f(X - 2, Y) + f(X + 2, Y)
Z = (Z > 0.4).astype(np.float32)
Z *= np.random.rand(*Z.shape)
for i, x in enumerate(x_vals):
for j, y in enumerate(y_vals):
color = f"{hex(int(Z[j, i] * 255))[2:]}"
if color == "0":
color = "#f00"
color = "#003"
else:
color = "#" + 3 * color
plt.fill([x, x + 0.1, x + 0.1, x], [y, y, y + 0.1, y + 0.1], color=color)
nb_cams = 32
cam_poses = np.array(
[[6 * np.cos(theta), 6 * np.sin(theta)] for theta in np.linspace(0, 2 * np.pi, nb_cams, endpoint=False)]
@ -44,31 +43,30 @@ for i in range(nb_cams):
plt.text(cam_poses[i][0], cam_poses[i][1], str(i))
x = np.array([[0, 0, 1], [0.5, -0.2, 1], [0.5, 0.2, 1], [0, 0, 1]]).T
x = cam2world_projs[i] @ x
x /= x[2, :]
plt.plot(x[0, :], x[1, :], "r-")
plt.xlim(-7, 7)
plt.ylim(-7, 7)
plt.axis("equal")
plt.savefig("data/peanut/peanut.png", dpi=300, bbox_inches="tight", pad_inches=0, transparent=True)
plt.close()
# draw 1d image of the scene for each camera
for i in range(2):
plt.figure()
for i in range(13, 21):
# sort pixels by distance to camera
cam_pose = cam_poses[i]
pixels_dist = np.linalg.norm(np.array([X.flatten(), Y.flatten()]).T - cam_pose, axis=1)
pixels_sort = np.argsort(pixels_dist)[::-1]
px = np.array([[-5, -5, 1], [5, -5, 1], [5, 5, 1], [-5, 5, 1]]).T
px = np.linalg.inv(cam2world_projs[i]) @ px
px /= px[1, :]
x0 = -1
x1 = 1
x0 = px[1, :].min()
x1 = px[1, :].max()
plt.fill([x0, x1, x1, x0], [0, 0, 1, 1], color="r")
plt.figure(f"img{i}")
plt.fill([x0, x1, x1, x0], [0, 0, 0.2, 0.2], color="#000")
plt.figure(f"mask{i}")
plt.fill([x0, x1, x1, x0], [0, 0, 0.2, 0.2], color="#000")
for j in pixels_sort:
x, y = X.flatten()[j], Y.flatten()[j]
@ -79,12 +77,26 @@ for i in range(2):
px = np.array([[x, y, 1], [x + 0.1, y, 1], [x + 0.1, y + 0.1, 1], [x, y + 0.1, 1]]).T
px = np.linalg.inv(cam2world_projs[i]) @ px
px /= px[1, :]
px /= px[0, :]
x0 = px[1, :].min()
x1 = px[1, :].max()
plt.fill([x0, x1, x1, x0], [0, 0, 1, 1], color=color)
plt.axis("equal")
plt.figure(f"img{i}")
plt.fill([x0, x1, x1, x0], [0, 0, 0.2, 0.2], color=color)
plt.figure(f"mask{i}")
plt.fill([x0, x1, x1, x0], [0, 0, 0.2, 0.2], color="#fff")
plt.show()
plt.figure(f"img{i}")
plt.xlim(-1, 1)
plt.ylim(0, 0.2)
plt.axis("off")
plt.savefig(f"data/peanut/images/Image{i:04}.png", dpi=300, bbox_inches="tight", pad_inches=0, transparent=True)
plt.close()
plt.figure(f"mask{i}")
plt.xlim(-1, 1)
plt.ylim(0, 0.2)
plt.axis("off")
plt.savefig(f"data/peanut/masks/Image{i:04}.png", dpi=300, bbox_inches="tight", pad_inches=0, transparent=True)
plt.close()

224
src/sfs2d.py Normal file
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@ -0,0 +1,224 @@
import numpy as np
import cv2
import matplotlib.pyplot as plt
from itertools import product
from rich.progress import track
from borders import update_border
from fvi import fast_voxel_intersect
x_vals = np.linspace(-5, 5, 100)
y_vals = np.linspace(-5, 5, 100)
VOXEL_SIZE = 0.1
X_MIN, X_MAX = -5, 5
Y_MIN, Y_MAX = -5, 5
def plot_camera(cam2world_proj, name, color):
points = np.array([[0, 0, 1], [0.5, -0.2, 1], [0.5, 0.2, 1], [0, 0, 1]]).T
points = cam2world_proj @ points
plt.plot(points[0, 0], points[1, 0], color=color, marker="o")
plt.plot(points[0, :], points[1, :], color=color, linestyle="-")
plt.text(points[0, 0], points[1, 0], s=name, color=color)
def plot_voxels(voxels, color, alpha, background):
if background:
plt.fill([X_MIN, X_MAX, X_MAX, X_MIN], [Y_MIN, Y_MIN, Y_MAX, Y_MAX], color="#000")
for i, j in np.argwhere(voxels):
x, y = X_MIN + i * VOXEL_SIZE, Y_MIN + j * VOXEL_SIZE
plt.fill([x, x + VOXEL_SIZE, x + VOXEL_SIZE, x], [y, y, y + VOXEL_SIZE, y + VOXEL_SIZE], color=color, alpha=alpha)
nb_frame = 32
points = np.array(
[
[x, y, 1.0]
for x, y in product(
np.arange(X_MIN, X_MAX, VOXEL_SIZE),
np.arange(Y_MIN, Y_MAX, VOXEL_SIZE),
)
]
)
cam_poses = np.array(
[[6 * np.cos(theta), 6 * np.sin(theta)]
for theta in np.linspace(0, 2 * np.pi, nb_frame, endpoint=False)]
)
cam_rots = np.linspace(np.pi, 3 * np.pi, nb_frame, endpoint=False)
cam2world_projs = np.array(
[
[[np.cos(theta), -np.sin(theta), cam_pose[0]],
[np.sin(theta), np.cos(theta), cam_pose[1]], [0, 0, 1]]
for theta, cam_pose in zip(cam_rots, cam_poses)
]
)
mask = 255
positions = []
proj_mats = []
frames = []
for k in range(nb_frame):
frame = cv2.imread(
f"data/peanut/masks/Image{k:04}.png", cv2.IMREAD_GRAYSCALE)[0, :]
frames.append(cv2.imread(f"data/peanut/images/Image{k:04}.png", cv2.IMREAD_GRAYSCALE)[0, :])
# print(f"frame.shape: {frame.shape}")
RT = np.linalg.inv(cam2world_projs[k])[:-1, :]
# a = np.array([0.0, 0.0, 1.0])
cam_points = RT @ points.T
cam_points /= cam_points[0]
cam_points += np.array([[0], [1.0]])
cam_points *= 0.5 * np.array([[1], [frame.shape[0]]])
cam_points = np.round(cam_points).astype(np.int32)
# print(f"cam_points: {cam_points}")
visible = np.logical_and.reduce(
(
0 <= cam_points[1, :],
cam_points[1, :] < frame.shape[0],
)
)
cam_points = cam_points[:, visible]
points = points[visible, :]
solid = frame[cam_points[1, :]] == mask
cam_points = cam_points[:, solid]
points = points[solid, :]
voxel = np.zeros((int((X_MAX-X_MIN)/VOXEL_SIZE), int((Y_MAX-Y_MIN)/VOXEL_SIZE)))
idx = np.floor_divide(points[:, :2] - np.array([X_MIN, Y_MIN]), VOXEL_SIZE).astype(int)
voxel[idx[:, 0], idx[:, 1]] = 1
def f(x, y):
return np.exp(-((x**2) + y**2) / 3)
x_vals = np.linspace(-5, 5, 100)
y_vals = np.linspace(-5, 5, 100)
X, Y = np.meshgrid(x_vals, y_vals)
Z = f(X - 2, Y) + f(X + 2, Y)
Z = (Z > 0.4).astype(np.float32)
Z = np.swapaxes(Z, 0, 1)
plt.figure()
plt.axis("equal")
plot_voxels(Z, "#fff", 1.0, True)
plot_voxels(voxel, "#00f", 0.5, False)
for i in range(nb_frame):
plot_camera(cam2world_projs[i], str(i), "#f00")
origin = np.array([X_MIN, Y_MIN])
step = np.array([VOXEL_SIZE, VOXEL_SIZE])
shape = np.array([int((X_MAX-X_MIN)/VOXEL_SIZE), int((Y_MAX-Y_MIN)/VOXEL_SIZE)])
for _ in range(5):
border = update_border(voxel)
plt.figure()
plt.axis("equal")
plot_voxels(voxel, "#fff", 1.0, True)
# plot_voxels(border, "#00f", 0.5, False)
for i in range(nb_frame):
plot_camera(cam2world_projs[i], str(i), "#f00")
for i, j in track(np.argwhere(border)):
x, y = X_MIN + i * VOXEL_SIZE, Y_MIN + j * VOXEL_SIZE
start = np.array([x, y]) + 0.5 * step
# plt.fill([x, x + VOXEL_SIZE, x + VOXEL_SIZE, x], [y, y, y + VOXEL_SIZE, y + VOXEL_SIZE], "#0f0", alpha=0.7)
values = []
for k in range(nb_frame):
# plot_camera(cam2world_projs[k], str(k), "#0f0")
end = cam_poses[k]
_, _, voxels_intersected = fast_voxel_intersect(start, end, origin, step, shape)
voxels_intersected = np.array(voxels_intersected, dtype=np.int32)
# for voxel_id in voxels_intersected:
# if not voxel[voxel_id[0], voxel_id[1]]:
# continue
# plt.fill(
# [
# origin[0] + voxel_id[0] * step[0],
# origin[0] + (voxel_id[0] + 1) * step[0],
# origin[0] + (voxel_id[0] + 1) * step[0],
# origin[0] + voxel_id[0] * step[0],
# ],
# [
# origin[1] + voxel_id[1] * step[1],
# origin[1] + voxel_id[1] * step[1],
# origin[1] + (voxel_id[1] + 1) * step[1],
# origin[1] + (voxel_id[1] + 1) * step[1],
# ],
# color="#f00",
# alpha=0.3,
# )
if len(voxels_intersected) == 0:
visible = True
else:
visible = voxel[voxels_intersected[:, 0], voxels_intersected[:, 1]].sum() == 0
if visible:
RT = np.linalg.inv(cam2world_projs[k])[:-1, :]
proj = RT @ np.array([start[0], start[1], 1.0])
proj /= proj[0]
proj += np.array([0, 1.0])
proj *= 0.5 * np.array([1, frames[k].shape[0]])
proj = np.round(proj).astype(np.int32)
values.append(frames[k][proj[1]])
# plt.figure()
# plt.imshow(np.repeat(frames[k][np.newaxis, :], 100, axis=0), cmap="gray")
# plt.plot(proj[1], 50, "ro")
# plt.show()
# else:
# plot_camera(cam2world_projs[k], str(k), "#f00")
if np.std(values) < 2.0:
voxel[i, j] = 1
color = "#0f0"
else:
voxel[i, j] = 0
color = "#f00"
plt.fill(
[
origin[0] + i * step[0],
origin[0] + (i + 1) * step[0],
origin[0] + (i + 1) * step[0],
origin[0] + i * step[0],
],
[
origin[1] + j * step[1],
origin[1] + j * step[1],
origin[1] + (j + 1) * step[1],
origin[1] + (j + 1) * step[1],
],
color=color,
alpha=0.3,
)
plt.figure()
plt.axis("equal")
plot_voxels(Z, "#fff", 1.0, True)
plot_voxels(voxel, "#00f", 0.5, False)
plt.show()